Date on Master's Thesis/Doctoral Dissertation
8-2011
Document Type
Master's Thesis
Degree Name
M.S.
Department
Computer Engineering and Computer Science
Committee Chair
Rouchka, Eric Christian
Author's Keywords
Image registration; Gene expression images; In-situ hybridization
Subject
Image processing--Digital techniques; Image analysis; Gene expression--Research--Methodology
Abstract
In the age of high-throughput molecular biology techniques, scientists have incorporated the methodology of in-situ hybridization to map spatial patterns of gene expression. In order to compare expression patterns within a common tissue structure, these images need to be "registered" or organized into a common coordinate system for alignment to a reference or atlas images. We use three different image registration methodologies (manual; correlation based; mutual information based) to determine the common coordinate system for the reference and in-situ hybridization images. All three methodologies are incorporated into a Matlab tool to visualize the results in a user friendly way and save them for future work. Our results suggest that the user-defined landmark method is best when considering images from different modalities; automated landmark detection is best when the images are expected to have a high degree of consistency; and the mutual information methodology is useful when the images are from the same modality.
Recommended Citation
Saka, Ernur, "Image registration and visualization of in situ gene expression images." (2011). Electronic Theses and Dissertations. Paper 1249.
https://doi.org/10.18297/etd/1249
